Partners for a workshop on AI in pharma & biotech

World Trade Center Shamshabad & Genome Valley have partnered with The Federation of Asian Biotech Associations (FABA) and have organised a workshop on “Artificial Intelligence for Pharma and Biotech,” in collaboration with Science Gurus and the University of Hyderabad. The workshop started on December 11, 2023, and ended on December 16, 2023. 

The workshop began with opening remarks from Prof P Reddanna, Executive president of FABA. Dr Jagath Reddy Junutula of Science Gurus and Dr Bindu Madav Reddy from the University of Hyderabad delivered the welcome address. 

The first speaker Dr Krishnan Nandabalan, president and CEO of In- veniAI, delivered a talk on “Artificial Intelligence for Pharma and Biotech – From Hype to Reality.” During his talk, Dr Nandabalan shed light on the ever- evolving landscape of healthcare, the integration of Artificial Intelligence and Machine Learning (AI/ML), proving to be transformative. He also emphasised that a shift towards more in-silico work and reduced wet lab experimentation holds promise. He also highlighted various applications of AI ranging from innovating target and drug discovery to pre-IND development. 

Dr Sunu, Engineer, iSPIRT, delivered the keynote address on “Why Does Intelligence Need Data? Building the AI Nation.” Dr Sunu said that there is an urgent need for safe and secure collection of information, aligned with principles of consent, purpose limitation, and privacy. 

The day proceeded with the third speaker, Dr Vasudeva Varma, Principal Research Scientist, Brane Enterprises. He delivered a lecture on “Role of Gen AI and Large Language Models in Healthcare.” 

Dr Varma concluded his talk with the hurdles resulting in the adoption of Generative AI in healthcare, such as transparency, safety, ethics, and accountability. 

The last speaker of the day, Dr Luca Emili, Founder and CEO of In-SilicoTrials, spoke about “Applications, Modeling, and Simulation for Pharma and Life Sciences.” Dr Luca shed light on the inherent challenges faced in the development of computation- al models.